The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Energy costs typically represent one of the largest ongoing expenses associated with a business enterprise's commercial leases. As a result, business enterprises and other institutions are increasingly looking to some form of automated energy management solution in an attempt to monitor and reduce costs associated with energy usage at commercially operated sites, while still maintaining the premises at temperature levels that are appropriate for workers and the then-current weather, climate and/or season.
For business enterprises such as small footprint retail and food service chains that may operate a large number of sites across a wide geographic area, past energy management solutions have had serious shortcomings. For example, according to industry studies, only a small percentage of small footprint commercial sites are automated with a computer-based energy management system. Instead, the vast majority of commercial sites are equipped with outdated manual or programmable thermostats that typically require configuration and management by a local site manager or other employees. However, a typical site manager is often saddled with a variety of other job responsibilities that leave few resources to properly configure and manage thermostats and other energy management devices for optimal energy usage. The financial implications of this mismanagement are potentially considerable, particularly for enterprises that control hundreds or thousands of sites.
Of the commercial sites that have an energy management system, these systems are typically implemented as costly, custom-designed solutions that target individual site locations and are often bundled with expensive professional services to maintain the systems. The prior energy management approaches have been a poor fit for business enterprises that manage a large number of small footprint sites by failing to provide a scalable energy management system that provides centralized control of an enterprise's energy management devices across multiple sites, and that enables valuable analysis and insight into an enterprise's energy usage across site boundaries in order to optimize energy usage.
Further, these systems fail to account for weather conditions other than temperature that can affect people's perception of the temperature. Changing seasons or other weather conditions can cause people to perceive the same indoor temperature as too hot or too cold. People then react by manually adjusting thermostats, thus reducing an energy savings attributable to the energy management system. Some programmable thermostats can use user interactions with the thermostat to implement behavioral learning.